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A People Counting System based on Face Detection and Tracking in a Video

Xi Zhao 1 Emmanuel Dellandréa 1 Liming Chen 1 
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Vision-based people counting systems have wide potential applications including video surveillance and public resources management. Most works in the literature rely on moving object detection and tracking, assuming that all moving objects are people. In this paper, we present our people counting approach based on face detection, tracking and trajectory classification. While we have used a standard face detector, we achieve face tracking combining a new scale invariant Kalman filter with kernel based tracking algorithm. From each potential face trajectory an angle histogram of neighboring points is then extracted. Finally, an Earth Mover's Distance-based K-NN classification discriminates true face trajectories from the false ones. Experimented on a video dataset of more than 160 potential people trajectories, our approach displays an accuracy rate up to 93%.
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Submitted on : Tuesday, January 17, 2017 - 1:56:46 PM
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Xi Zhao, Emmanuel Dellandréa, Liming Chen. A People Counting System based on Face Detection and Tracking in a Video. 6th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Sep 2009, Genova Italy. pp.67-72, ⟨10.1109/AVSS.2009.45⟩. ⟨hal-01437717⟩



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